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Record W2064313527 · doi:10.4212/cjhp.v67i5.1388

Learning and Networking: Utilization of a Primary Care Listserv by Pharmacists

2014· article· en· W2064313527 on OpenAlexafffundvenueabout
Melanie Trinacty, Barbara Farrell, Theresa J. Schindel, Lisa Sunstrum, Lisa Dolovich, Natalie Kennie‐Kaulbach, Grant Russell, Nancy M. Waite

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsDalhousie UniversityCanadian Pharmacists AssociationUniversity of WaterlooUniversity of AlbertaBruyèreMcMaster University Medical CentreOttawa Hospital
FundersUniversity of Waterloo
KeywordsSpecialtyPsychologyPharmacyPrimary careMentorshipCoding (social sciences)Content analysisMedical educationFamily medicineNursingMedicine

Abstract

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Background: Expanding into new types of practice, such as family health teams, presents challenges for practising pharmacists. The Primary Care Pharmacy Specialty Network (PC-PSN) was established in 2007 to support collaboration among pharmacists working in primary care. The PC-PSN offers to its members a listserv (also referred to as an electronic mailing list) jointly hosted by the Canadian Society of Hospital Pharmacists and the Canadian Pharmacists Association.Objectives: To characterize PC-PSN membership and participation in the listserv and to examine how the listserv is used by analyzing questions posted, concerns raised, and issues discussed.Methods: Qualitative content analysis was used to examine 1 year of archived PC-PSN listserv posts from the year 2010. Two coders used NVivo software to classify the content of posts. Research team members reviewed and discussed the coding reports to confirm themes emerging from the data.Results: Overall, 129 people (52.9% of the 244 listserv members registered at the end of the calendar year) posted to the listserv during the study period. These participants worked in various practice settings, with over half residing in Ontario (68/129 [52.7%]). A total of 623 posts were coded. Agreement between coders, for a sample of posts from 10 users, was acceptable (kappa = 0.78). The listserv was used to share information on a diverse set of topics, to support decision-making and acquire solutions for complex problems, and as a forum for mentorship.Conclusions: The qualitative content analysis of the PC-PSN listserv posts for the year 2010 showed that the listserv was a medium for information-sharing and for providing and receiving support, through mentorship from colleagues. Apparent learning needs included effective question-posing skills and application of evidence to individual patients.RÉSUMÉContexte : Passer à de nouveaux types de pratiques, comme les groupes de médecine de famille, présente différents défis pour les pharmaciens en exercice. Le Réseau de spécialistes en pharmacie (RSP) en soins de santé primaires a été mis sur pied en 2007 dans le but de favoriser la collaboration entre pharmaciens oeuvrant en soins de santé primaires. Le RSP en soins de santé primaires offre à ses membres un gestionnaire de liste de diffusion (listserv) sous l’égide conjoint de la Société canadienne des pharmaciens d’hôpitaux et de l’Association des pharmaciens du Canada.Objectifs : Offrir un portrait des effectifs du RSP en soins de santé primaires et de la participation des membres au forum de discussion, et étudier comment le gestionnaire de liste de diffusion est utilisé à l’aide d’une analyse des questions publiées, des préoccupations soulevées et des problèmes abordés.Méthodes : Une analyse qualitative du contenu a servi à étudier l’ensemble des messages archivés dans le gestionnaire de liste de diffusion de l’année 2010. Deux codeurs ont utilisé le logiciel NVivo pour classer le contenu des messages publiés. Les résultats de l’encodage ont été examinés par les membres de l’équipe de recherche afin d’identifier les thèmes se dégageant des données.Résultats : Dans l’ensemble, 129 personnes (52,9 % des 244 membres inscrits au gestionnaire de liste de diffusion à la fin de l’année civile) ont publié des messages durant la période à l’étude. Les participants travaillaient dans différents milieux et plus de la moitié habitaient en Ontario (68/129 [52,7 %]). Au total, 623 messages ont été encodés et la concordance entre les résultats des deux codeurs était satisfaisante pour un échantillon de messages provenant de 10 usagers (indice kappa = 0,78). Le gestionnaire de liste de diffusion a servi à partager de l’information sur une gamme de sujets, à appuyer des prises de décision et à trouver des solutions à des problèmes complexes. Il a aussi servi de forum de mentorat.Conclusions : L’analyse qualitative du contenu des messages publiés en 2010 dans le gestionnaire de liste de diffusion par les membres du RSP en soins de santé primaires a montré que le gestionnaire est un média d’échange d’information et qu’il permet d’offrir et de recevoir du soutien grâce au mentorat entre collègues. Parmi les besoins identifiés, on compte la capacité à bien formuler des questions et l’application des données probantes pour le traitement individuel des patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.998
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.001
Scholarly communication0.0020.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.261
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations12
Published2014
Admission routes4
Has abstractyes

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